Buzz
When predicting the number of events occurring within a specific time, one cannot overlook the utility of the POISSON function. This article provides a detailed guide on how to use the POISSON function, which calculates the Poisson distribution.
Description: The POISSON function is the foundation for determining the Poisson distribution, serving as a basis for estimating the number of events within a specified time period. For example, predicting the density of cars passing through a toll booth on weekends in a minute. Anticipating such events allows for specific supportive measures.
Syntax: POISSON(x, mean, cumulative).
In this context:
- x: The number of events, a mandatory parameter.
- mean: The value to be estimated (numeric value), a mandatory parameter.
- cumulative: A logical value determining the form of the returned value. It can take the following values:
+ If cumulative = TRUE => the function returns the cumulative Poisson probability that 0 < the number of events <= x
+ If cumulative = FALSE: the function returns the Poisson probability that the number of events = x.
Note:
- The Poisson function is calculated using the formula:
+ If cumulative = TRUE:
+ If cumulative = FALSE:
- If x is a decimal number, the function rounds it to the nearest integer.
- Both x and the mean must be numeric; otherwise, the function returns an error #VALUE.
- If x is less than 0, the function returns the error value #NUM!.
- If mean is less than 0, the function returns the value #NUM!.
Example:
- Calculate Poisson when cumulative = True:
Enter the formula in the cell where you want to calculate: =POISSON(D13,D14,D15).
Press Enter, and the result is:
- Calculate Poisson when cumulative = False:
Enter the formula in the cell where you want to calculate: =POISSON(D13,D14,D16).
Press Enter, and the result is:
So, the Poisson function yields different results based on the cumulative value. Hopefully, the Poisson function proves helpful for you in predicting events within a specified time frame.
Wishing you all success!
